Bibliographic record
Abstract
Cet article étudie les problèmes fondamentaux qui se posent aux traducteurs de tous lestemps et de tous les pays. Par une comparaison succincte des réflexions théoriqueschinoises et françaises sur la traduction, l'auteur souligne la similitude et l'oppositiondualiste entre traduction libre et littérale qui se perpétue à travers le temps et l'espace. Ledébat sur la retraduction du Rouge et le Noir en Chine en offre un parfait exemple. Poursortir de cette opposition dualiste dans les études de traduction, l'auteur propose uneétude des niveaux de traduction, en analysant les éléments interdépendants et interactifsdes trois niveaux de la traduction : le niveau de pensée, le niveau sémantique et le niveauesthétique. Le but est donc d'ouvrir un domaine ou un nouvel angle de réflexion sur lanature et le processus de la traduction, et d'en mesurer objectivement la complexité et latâche pour avoir une conscience plus juste des problèmes fondamentaux du traduire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".